About Me

I am a PhD candidate in Condensed Matter Physics at the University of Edinburgh, working in the group of Professor Elton J. G. Santos. My research bridges the gap between theoretical models and experimental findings to unlock the potential of 2D van der Waals (vdW) magnetic materials for energy-efficient spintronic applications.

My Academic Journey

I began my academic career at the University of Central Florida, where I earned a dual Bachelor of Science in Physics and Mathematics. During my undergraduate studies, I conducted research under Professor Richard Klemm, focusing on wave functions for high-symmetry, 2D microstrip antennas. I designed programs to analyze symmetry patterns, notably identifying C3vC_{3v} wave function symmetries in equilateral triangular boundary systems.

Subsequently, I completed my MSc in Physics with Distinction at Imperial College London, exploring the applications of Spin Torque Nano-Oscillators (STNOs) for artificial neural networks.

Current Work

Currently, I utilize high-performance computing (HPC) clusters like Archer2, Cirrus, and DiRAC to conduct advanced atomistic (VAMPIRE) and micromagnetic (MUMAX3) simulations. My goal is to elucidate the intrinsic properties of 2D vdW magnets (like Fe3GeTe2\text{Fe}_3\text{GeTe}_2 and CrTe2\text{CrTe}_2) and investigate the dynamic evolution of skyrmions. I collaborate closely with international researchers to provide theoretical validation for topological phase transitions, spin-orbit torque injection, and magnetization reversal mechanisms.

Beyond physics, I am an avid PC hardware enthusiast. I enjoy building custom workstations, optimizing power efficiency at the BIOS level, managing Arch Linux homelab environments, and exploring network privacy.

Research Interests

My core research focus includes: Computational Magnetism, 2D van der Waals Magnets, Skyrmions and Topological Spin Textures, Micromagnetic Simulations, and High-Performance Computing.

“Understanding the fundamental limits and thermodynamics of topological spin textures is the key to designing the next generation of energy-efficient computing paradigms.”